In 2005, a group of veteran litigation support professionals came together and developed the standard reference model for the lifecycle of eDiscovery today -the Electronic Discovery Reference Model (EDRM). While the phases of eDiscovery are virtually unchanged, the way eDiscovery is performed today is radically different from where it began. The emergence of analytics, automation and artificial intelligence/machine learning algorithms (AI) have revolutionized how eDiscovery is conducted and this technology is now poised to similarly transform the way the industry analyzes contracts.
Analytical capabilities have been available for more than a decade but hadn’t made it to prime time in legal technology until more recently.
The adoption of Concept Clustering (to group similar documents together), Email Thread Identification (to avoid reviewing the same emails repeatedly) and Language Identification (to identify potential foreign language review needs), are now standard components in a typical eDiscovery workflow.
Magistrate Judge Andrew Peck’s ruling over nine years ago in Da Silva Moore v. Publicis Groupe & MSL Group, approving the use of “computer-assisted review” was a catalyst for the proliferation of Predictive Coding algorithms.
The arrival of data visualizations shined a light on analytics and the power of transparency it brought with Cluster Wheels, Dashboards and Communication Visualizations, allowing the industry to dive deeper and interrogate data through multiple dimensions. While analytics have contributed to revolutionizing the eDiscovery process, it has taken knowledgeable and experienced eDiscovery Subject Matter Experts (SMEs) to maximize the capabilities of these tools and incorporate them effectively into discovery workflows.
Converging eDiscovery Analytics with Contracts Experience
Like eDiscovery, contract analysis and related services are undergoing their own evolution. As is the case with eDiscovery, the ability to leverage predictive coding and other analytical tools, coupled with subject matter expertise, accelerates the extraction of critical information in a shorter timeframe and with greater precision. Additionally, because contract analytics has a broad application outside of the discovery process, here is a lower barrier to entry in terms of legal professional acceptance, comfort with sampling and verification methodologies, and ultimately adoption.
The contract analytics evolution can be viewed as the next step in the EDRM. There are clear synergies between eDiscovery analytics and contract analytics. Success in the contract analytics arena takes specific expertise, vision in understanding contracts as data, and fluency of the relevant legal issues to fully realize the cost, expediency, and outcome efficiencies.
What to Look for in a Contract Analytics Provider
The ability to bring together years of experience in streamlining and automating workflows in eDiscovery through leveraging analytics and AI, along with years of experience understanding the nuances of contract analysis, is key to identifying an effective contract analytics provider. Deep expertise in both areas is critical to ensure a successful contract analytics project.
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